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Item type:Publication, Access status: with files , Learning environmental field exploration with computationally constrained underwater robots : Gaussian processes meet stochastic optimal control(Multidisciplinary Digital Publishing Institute (MDPI), 2019-05-06); ; ; Autonomous exploration of environmental fields is one of the most promising tasks to be performed by fleets of mobile underwater robots. The goal is to maximize the information gain during the exploration process by integrating an information-metric into the path-planning and control step. Therefore, the system maintains an internal belief representation of the environmental field which incorporates previously collected measurements from the real field. In contrast to surface robots, mobile underwater systems are forced to run all computations on-board due to the limited communication bandwidth in underwater domains. Thus, reducing the computational cost of field exploration algorithms constitutes a key challenge for in-field implementations on micro underwater robot teams. In this work, we present a computationally efficient exploration algorithm which utilizes field belief models based on Gaussian Processes, such as Gaussian Markov random fields or Kalman regression, to enable field estimation with constant computational cost over time. We extend the belief models by the use of weighted shape functions to directly incorporate spatially continuous field observations. The developed belief models function as information-theoretic value functions to enable path planning through stochastic optimal control with path integrals. We demonstrate the efficiency of our exploration algorithm in a series of simulations including the case of a stationary spatio-temporal field.Publicationtype: Journal ArticleScopus© Citations 13 445 401 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , An integrated approach to navigation and control in micro underwater robotics using radio-frequency localizationNavigation and control are a largely unsolved problems for micro autonomous underwater vehicles (). The main challenges are due to the lack of accurate underwater localization systems, which fit on-board of . In this work, we present an integrated navigation and control architecture consisting of a low-cost embedded localization module and an underwater way-point tracking controller, which fulfills the requirements of . The performance of the navigation and control system is benchmarked in two different experimental scenarios.Publicationtype: Conference Paper211 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Design, dynamics, and control of micro underwater vehicle systems for autonomous environmental exploration(2019); This dissertation covers exploration and monitoring of environmental fields with micro underwater vehicles (μAUVs). The design of an underactuated μAUV is presented. Moreover, control concepts are introduced for trajectory tracking and path following. Two methods for underwater self-localization are presented, which are suitable for μAUVs. The first approach is based on time delays of arrival of acoustic signals. The second approach exploits attenuation of electro-magnetic signals in water. Lastly, an information theoretic control method is developed, which allows a fleet of μAUVs to explore environmental fields. The method combines stochastic optimal control with Gaussian Markov random fields.Publicationtype: Doctoral Thesis557 1063 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Micro underwater vehicle hydrobatics: a submerged furuta pendulum(IEEE, 2018-09); ; ; ; We present the new HippoCampus micro underwater vehicle, first introduced in [1]. It is designed for monitoring confined fluid volumes. These tightly constrained settings demand agile vehicle dynamics. Moreover, we adapt a robust attitude control scheme for aerial drones to the underwater domain. We demonstrate the performance of the controller with a challenging maneuver. A submerged Furuta pendulum is stabilized by HippoCampus after a swing-up. The experimental results reveal the robustness of the control method, as the system quickly recovers from strong physical disturbances, which are applied to the system.Publicationtype: Conference Paper329 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Low-cost monocular localization with active markers for micro autonomous underwater vehiclesWe present an approach for estimating the absolute poses of a swarm Micro Autonomous Underwater Vehicles (μAUVs) by decomposing the problem into few absolute position estimations and many relative pose estimations. As power constraints are critical to small mobile robots, we develop an extension of active marker pose estimation using color information to solve the marker correspondence problem, and show that this approach is more energy efficient than reflective estimation approaches. We show the feasibility of this approach by localizing a robot navigating in an underwater test tank environment. Detailed analysis is presented characterizing the noise and error properties when estimating robot poses from fixed on-board markers. Moreover, we provide comparisons in power and computational cost for other popular methods of underwater localization.Publicationtype: Conference Paper141 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Design and adaptive depth control of a micro diving agent(IEEE, 2017-06-09); ; ; ; This letter presents the depth control of an autonomous micro diving agent called autonomous diving agent (ADA). ADA consists of off-The-shelf components and features open-source hardware and firmware. It can be deployed as a testbed for depth controllers, as well as a mobile sensor platform for research or in industrial tanks.We introduce a control law that is based on the feedback linearization method and enhanced by an adaptive fuzzy algorithm to cope with modeling inaccuracies. The proposed depth controller is computationally light enough to run on ADAs embedded hardware. In experiments performed in a wave tank, the adaptive fuzzy scheme shows the ability to deal with both depth regulation and depth profile tracking. ADA is even able to hold on to dynamic isobars despite external disturbances. We demonstrate that under the influence of waves, ADA describes orbital motions similar to water particles.Publicationtype: Journal Article114 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Embedded spherical localization for micro underwater vehicles based on attenuation of electro-magnetic carrier signals(Multidisciplinary Digital Publishing Institute (MDPI), 2017-04-26); ; ; ; Self-localization is one of the most challenging problems for deploying micro autonomous underwater vehicles (μAUV) in confined underwater environments. This paper extends a recently-developed self-localization method that is based on the attenuation of electro-magnetic waves, to the μAUV domain. We demonstrate a compact, low-cost architecture that is able to perform all signal processing steps present in the original method. The system is passive with one-way signal transmission and scales to possibly large μAUV fleets. It is based on the spherical localization concept. We present results from static and dynamic position estimation experiments and discuss the tradeoffs of the system.Publicationtype: Journal ArticleScopus© Citations 17 710 671